Cargando…
Reinforcement Learning-Aided Edge Intelligence Framework for Delay-Sensitive Industrial Applications
With the advancement in next-generation communication technologies, the so-called Tactile Internet is getting more attention due to its smart applications, such as haptic-enabled teleoperation systems. The stringent requirements such as delay, jitter, and packet loss of these delay-sensitive and los...
Autores principales: | Zubair Islam, Muhammad, Shahzad, Ali, Rashid, Haider, Amir, Kim, Hyung Seok |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9609103/ https://www.ncbi.nlm.nih.gov/pubmed/36298353 http://dx.doi.org/10.3390/s22208001 |
Ejemplares similares
-
IoTactileSim: A Virtual Testbed for Tactile Industrial Internet of Things Services
por: Zubair Islam, Muhammad, et al.
Publicado: (2021) -
A Novel Blockchain Framework for Industrial IoT Edge Computing
por: Xu, Xuesong, et al.
Publicado: (2020) -
Industrial Needs in the Fields of Artificial Intelligence, Internet of Things and Edge Computing
por: Stadnicka, Dorota, et al.
Publicado: (2022) -
Edge-Sensitive Left Ventricle Segmentation Using Deep Reinforcement Learning
por: Xiong, Jingjing, et al.
Publicado: (2021) -
BlockEdge: A Privacy-Aware Secured Edge Computing Framework Using Blockchain for Industry 4.0
por: Guha Roy, Deepsubhra
Publicado: (2023)